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Record W2795282787 · doi:10.1101/240903

Visualization of class A GPCR oligomerization by image-based fluorescence fluctuation spectroscopy

2017· preprint· en· W2795282787 on OpenAlexfundno aff
Ali Işbilir, Jan Møller, Andreas Böck, Ulrike Zabel, Paolo Annibale, Martin J. Lohse

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2017
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsnot available
FundersJulius-Maximilians-Universität WürzburgUniversité Laval
KeywordsG protein-coupled receptorFluorescence spectroscopyChemistryReceptorBiophysicsComputational biologyFluorescenceBiochemistryBiologyPhysics

Abstract

fetched live from OpenAlex

Abstract G protein-coupled receptors (GPCRs) represent the largest class of cell surface receptors conveying extracellular information into intracellular signals. Many GPCRs have been shown to be able to oligomerize and it is firmly established that Class C GPCRs (e.g. metabotropic glutamate receptors) function as obligate dimers. However, the oligomerization capability of the larger Class A GPCRs (e.g. comprising the β-adrenergic receptors (β-ARs)) is still, despite decades of research, highly debated. Here we assess the oligomerization behavior of three prototypical Class A GPCRs, the β 1 -ARs, β 2 -ARs, and muscarinic M 2 Rs in single, intact cells. We combine two image correlation spectroscopy methods based on molecular brightness, i.e. the analysis of fluorescence fluctuations over space and over time, and thereby provide an assay able to robustly and precisely quantify the degree of oligomerization of GPCRs. In addition, we provide a comparison between two labelling strategies, namely C-terminally-attached fluorescent proteins and N-terminally-attached SNAP-tags, in order to rule out effects arising from potential fluorescent protein-driven oligomerization. The degree of GPCR oligomerization is expressed with respect to a set of previously reported as well as newly established monomeric or dimeric control constructs. Our data reveal that all three prototypical GPRCs studied display, under unstimulated conditions, a prevalently monomeric fingerprint. Only the β 2 -AR shows a slight degree of oligomerization. From a methodological point of view, our study suggests three key aspects. First, the combination of two image correlation spectroscopy methods allows addressing cells transiently expressing high concentrations of membrane receptors, far from the single molecule regime, at a density where the kinetic equilibrium should favor dimers and higher-order oligomers. Second, our methodological approach, allows to selectively target cell membrane regions devoid of artificial oligomerization hot-spots (such as vesicles). Third, our data suggest that the β 1 -AR appears to be a superior monomeric control than the widely used membrane protein CD86. Taken together, we suggest that our combined image correlation spectroscopy method is a powerful approach to assess the oligomerization behavior of GPCRs in intact cells at high expression levels.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.241
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2017
Admission routes1
Has abstractyes

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